Business in the Driver’s Seat – An Improved Model for Integration
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Transcript of Business in the Driver’s Seat – An Improved Model for Integration
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The Briefing Room
Business in the Driver’s Seat – An Improved Model for Integration
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The Briefing Room
! Reveal the essential characteristics of enterprise software, good and bad
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! Give vendors a chance to explain their product to savvy analysts
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Mission
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Topics
2014 Editorial Calendar at www.insideanalysis.com/webcasts/the-briefing-room
This Month: INTEGRATION & DATA FLOW
October: ANALYTIC PLATFORMS
November: DISCOVERY & VISUALIZATION
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Executive Summary The Great Divide • The IT/Biz Divide Must End • Agile, Not Waterfall • Iterating Must Be Easy • Collaboration is Mandatory
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Analyst: Robin Bloor
Robin Bloor is Chief Analyst at The Bloor Group
[email protected] @robinbloor
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WhereScape
! WhereScape is a data warehousing software company
! It offers WhereScape 3D, software for planning and reality-testing data warehousing and business intelligence projects; and WhereScape RED, an integrated development environment used for building, deploying and managing data warehouses and data marts.
! WhereScape RED allows developers to automate the data warehousing life cycle
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Guest: Mark Budzinski
Mark Budzinski is the President of WhereScape. In this role, Mark sees firsthand the challenges that IT organizations face and their desire to better serve the business community with agile, rapid development of data warehouses and related data driven projects. His career has spanned management positions at Intel, Sequent Computer Systems, RadiSys, and Applied Microsystems. He holds an MBA from the Univ. of Oregon, a Master’s Degree in Computer Science from the University of Southern California, a BS in Industrial Engineering from Lehigh University, and is a graduate of The Buckley School of Public Speaking.
Mark Budzinski
President
WhereScape
WhereScape Bloor Group Briefing Room
Data Integration: It Can be Fast and Agile
September 30, 2014
Let’s Talk About the Elephant in the Room
¡ IT has its hands full
¡ New data sources abound
¡ The business employs all kinds of tricks to work around IT
¡ We hide the whole mess in human capital ¡ Consultants (hand coding) ¡ Politics ¡ Excuses
WhereScape: What We Believe
The historical record that “data warehouses
take too long to build and are too hard to
change” must evolve to a paradigm whereby
IT delivers value continuously, manages
ongoing changes cost effectively, and
mitigates risk throughout
WhereScape: What We Believe
¡ Getting the data right is critically important, yet business users can seldom articulate what they want until they see it
¡ Business users/consumers of data must be served at their pace
¡ Automate as much of the process as possible
¡ Standards matter
¡ Document everything; later changes demand it
ETL Is Not The Same Thing As…
Move Data
Transform Data
Load Data From Sources including OLTP, files, Hadoop, etc.
Create Database Objects
such as Models, Views, Facts, Dimensions, Indexes
Documentation
WhereScape Value Proposition
¡ We empower IT organizations to build, deploy, and manage their data in a timeframe and manner that creates utter enthusiasm in the business community
¡ Time to results dramatically decreases - faster
¡ Costs decrease: license and human capital - cheaper
¡ Quality is higher: documentation & transparency - better
¡ Risk is mitigated: automation & methodology – with confidence
By automating development, you get more from your “data investment”
Data Warehouse Automation Software: RED
RED is an Automated Data Warehouse Development Platform That Builds Native Target Database Objects, Documents Them, And Schedules Data To Be Loaded. RED Works Well With ETL Tools, or as an ELT Solution Using Native Loaders (e.g. Teradata TPT)
Automation Use Cases
End-to-End Data Warehouse
Development Tool
Including All ETL
Complement to Enterprise ETL, Used
For Rapid/Agile Build Out of a View or Semantic Layer
Green Field
Clean Up Hand-Written
Code and Scripts
Manage Deployments
Rewrite & Recast Heterogeneous
Database Solutions
Big Data Integration
ELT 2.0
Configuration Management
Semantic Layer
Some of Our Customers
“WhereScape RED’s tight integration with the target database and built-in best practices are empowering our resource-constrained development team to tackle a large implementation that will enable us to quickly deliver value to our institution and members.”
Su Rayburn, Director of Business Intelligence Services
“Our results using WhereScape have been extremely impressive. WhereScape enabled us to design, develop, document and deploy a production-ready solution in 6-8 weeks. Using traditional data warehouse development methods would have taken us 6-8 months.
Ryan Fenner, VP, Data Solutions Architect, Union Bank
“We estimate the development lifecycle is 20-25% of what it was previously when we were hand coding.”
Dan Mosher, Director of Enterprise Data Warehousing
Summary
WhereScape’s approach with data warehouse automation yields customer results that are stunning: faster, cheaper, and more manageable
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The Briefing Room
Perceptions & Questions
Analyst: Robin Bloor
ETL or a Jumble of Pipes?
Robin Bloor, PhD
In the Era of Big Data
u More data has become available: • Via social media • From public sources • From commercial sources • From log files • From unstructured sources • Through better data harvesting
u And it is arriving faster!! u And users expect it to be
available faster…
Data Flow – The New Reality
u A good deal of the new data is EXTERNAL to the business
u This means that the data warehouse is becoming LARGER AND MORE COMPLEX
u It also means more need for DEFINING AND REFINING the data before it hits the warehouse
u MANAGING the data flow itself has become a necessity – better to avoid ETL spaghetti
What Does Big Data Mean to the D/W?
The Data Warehouse Challenges…
u The data flow and data warehouse architecture cannot be completely separate.
u Data ingest is a far bigger problem than it once was
u The data model changes far more often
u Data warehouse construction and maintenance are more difficult and more time consuming
Data Warehouse Automation
At the moment data warehouse creation and maintenance is often a
MANUAL activity
It is becoming TOO COMPLEX to remain a manual activity
u It is clear (to me) how RED can have a big impact in creating a new data warehouse. How can it be used if you already have a DW and simply want to improve its operation?
u Does RED “play well with others?” Which databases/ETL products does it work with?
u What do you see as the sweet spot for RED? What size of company/size of problem?
u What does RED actually compete with? Are there other products that do end-to-end DW Building & Maintenance?
u Does RED “go large?” In respect of scale, what is your largest implementation of RED by data volumes?
u How do you complement/work with Hadoop?
u Does RED help with data mart creation & maintenance?
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Upcoming Topics
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2014 Editorial Calendar at www.insideanalysis.com/webcasts/the-briefing-room
This Month: INTEGRATION & DATA FLOW
October: ANALYTIC PLATFORMS
November: DISCOVERY & VISUALIZATION
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THANK YOU for your
ATTENTION!
Opening slide image courtesy of Wikimedia Commons